With recent advancements in transportation and logistics, security, surveillance, and consumer focused transportation network, an ever mutating demand is witnessed that necessitates these industries to adopt autonomous and intelligent solutions to counter different challenges put forth with such advancements. Multiple imaging sensors are traditionally used to capture images of objects and path in vicinity of the vehicles. In certain scenarios, a vehicle having an imaging sensor, may be in motion. In cases where the vehicle, such as an autonomous vehicle, uses CMOS-like sensor to capture images and analyze the captured images frame by frame, the effect of rolling shutter is introduced due to the motion of the vehicle. When the vehicle that carries the imaging sensors moves fast relative to the objects in the vicinity, the rolling shutter effect may be more prominent in the captured images, which is not desirable. The rolling shutter effect can possibly cause regions or objects captured in the image to wobble, skew, smear, or have a partial exposure. Therefore, the images obtained from the imaging sensor while the vehicle is in motion may not be suited for further application in numerous image processing operations, such as prediction of position or movement of other objects in a scene, calibration of speed or orientation of the vehicle. Moreover, the use of such images of degraded image quality may lead to poor estimations and can endanger lives, cause delay, compromise the safety, and may prove cost intensive.
Traditionally, such effects on images are compensated using multiple sensors, such as motion, speed, location, acceleration, or gyro, as peripheral connections to the imaging sensors to compensate for the degradation of the image. Such solutions are further available only for low speed applications or where the effect is caused by vibrations of engine or other holding devices. Therefore, such solutions are not compatible for relatively fast moving vehicles. Also, the effects on the images are compensated only after the image is captured and therefore, there is an inherent delay in compensation of the images which is further reciprocated to other image processing systems of the vehicle that factor driving decisions based on the compensated image. Alternatively stated, current solutions lack a real time on-chip compensation inside the imaging sensors.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of described systems with some aspects of the present disclosure, as set forth in the remainder of the present application and with reference to the drawings.